* Add ScaleDown model pricing
Registers the five ScaleDown models in the pricing map. ScaleDown bills on
input tokens only, so output_cost_per_token is zero for every entry. The
classify and decisions models bill at $0.04 per million input tokens, and
extract, summarize, and compress bill at $0.05 per million.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
* Price all ScaleDown models at $0.04 per million and drop unverified context limits
Every ScaleDown model now bills $0.04 per million input tokens. The
32000-token max_input_tokens/max_output_tokens values were not confirmed
against the service, so they are removed rather than registered.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
* Price all ScaleDown models at $0.05 per million input tokens
This is the standard rate in ScaleDown's billing and matches the usage dashboard.
The Decisions usage.cost field is not used for pricing.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
* Add regression tests for the ScaleDown pricing entries
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
* Cite the source of the ScaleDown rate in the pricing tests and type them
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
* Add ScaleDown as a chat provider
ScaleDown serves five models over two wire protocols. extract, summarize, and
compress speak OpenAI chat on /v1/chat/completions, while classify and
decisions implement the Jev Decisions API on /v1/scaledown, taking a state
object plus a questions map and returning one typed answer per question.
The provider authenticates with x-api-key rather than a bearer token, and the
decisions models need a non-chat request body, so it routes through the HTTP
handler instead of the OpenAI passthrough. Malformed decisions requests are
rejected locally with a message naming the problem, so callers do not have to
decode an opaque 422 from upstream. Decisions bills one model call per
question, so the cost upstream reports is passed through rather than
re-estimated from token counts.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
* Route ScaleDown domain models to the native API and stop trusting usage.cost
The /v1/chat/completions and /v1/models routes return 403 on api.scaledown.xyz,
so extract, summarize and compress now call the native /extract,
/summarization/abstractive and /compress/raw/ endpoints. The default api_base is
the bare host; a trailing /v1 is stripped and re-added only for decisions.
The Decisions usage.cost field was about 600x the dashboard amount, so it is no
longer passed through; cost is computed from input tokens at the registered rate.
Native responses are returned unchanged as JSON, including the _value/_span_anchor
wrappers on nested extraction. They carry no output token count, so
completion_tokens is reported as 0 and documented as unmeasured.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
* Move ScaleDown translation into llms/ and address review findings
- Dispatch moves to llms/scaledown/chat/handler.py; main.py keeps a thin call
and get_llm_provider_logic.py no longer has a ScaleDown branch, since the
config resolves key and base URL itself.
- questions passed via extra_body are merged and validated after the shared
merge (sign_request), so the documented extra_body path works.
- extra_body can no longer change the upstream model, and decisions state may
carry a document but not text, so guardrails always see the text.
- A custom api_base requires its own api_key; the environment key is only sent
to the default host or SCALEDOWN_API_BASE.
- Image content parts become the decisions document; max_completion_tokens maps
to max_tokens; stream is served as one chunk for every model.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
* Refuse prompt-bearing extra_body keys and empty-key fallback to the env credential
extra_body is merged after guardrails inspect the messages, so each model now
accepts only option keys there (extract threshold/top_n, compress
compression_rate, decisions questions/state); text, instructions, prompt,
context and model are rejected. An empty api_key no longer lets the
SCALEDOWN_API_KEY from the environment go to a custom api_base.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
* Read compress token usage from the real response shape
/compress/raw/ nests the per-prompt counts under results and reports the total
as a top-level input_tokens; the provider read a top-level original_prompt_tokens
that is not there, so compress reported zero tokens and zero cost.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
* Accept the router's max_retries and word the extra_body error clearly
The proxy adds max_retries to every call, which map_openai_params rejected, so
every proxied ScaleDown request failed with a 400. It is now accepted and not
forwarded.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
* Return extracted fields from extract, follow schema refs, and meet the type-discipline gate
- extract content is now the extracted fields (span anchors dropped, wrappers
unwrapped), so it validates against the caller's response_format; the raw
payload stays on _hidden_params['scaledown_response'].
- Local $ref/$defs in the response_format schema are resolved.
- The adapter is rewritten with Final locals, read-only annotations, one raising
helper and a typed handler; check_type_discipline reports no violations.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
* Fix stream_options, schema-guided extract cleaning, document input and multi-image handling
- stream_options is accepted and not sent upstream, so include_usage streams work.
- Extract output is cleaned against the requested entities, so a field named
_value or *_span_anchor is no longer dropped.
- Extract and summarize send an image or PDF as the native document fields.
- More than one image is rejected instead of silently using the first.
- The cost test derives its rate from the cost map.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
* Cut recursive schema refs at the cycle and cap the expanded entity count
A small response_format schema with a self-referencing $def expanded to 4^16
leaves before any request was sent. Refs that point back into themselves are now
cut off at that point, and the total expanded entities are capped at 1000 so
repeated acyclic refs are rejected with a clear error.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
* Bound ref chains and schema nesting so long schemas fail cleanly
Resolving a chain of thousands of distinct $refs recursed until RecursionError.
Ref resolution is now an iterative walk capped at 32 hops, and nested properties
are capped at 32 levels; both raise a clear 400 instead.
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
* fix(scaledown): support native classify and preserve extraction results
* test(scaledown): include provider regressions in CI shard
* fix(scaledown): pass registry typing and bounded recursion checks
* docs(scaledown): capture provider setup before and after
* fix(scaledown): preserve nullable schemas and reject malformed requests
* fix(scaledown): isolate provider dispatch from existing providers
* fix(scaledown): preserve the shared dispatch return contract
* fix(scaledown): preserve failure logging and reject lossy schemas
* fix(scaledown): keep timeout typing annotation on its expression
* fix(scaledown): resolve escaped extraction schema references
* fix(scaledown): annotate the bounded reference walk
* chore(scaledown): remove unused loop suppression
---------
Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
Co-authored-by: moe-berri <moe@berri.ai>
* refactor(types): move LitellmUserRoles and KeyManagementRoutes into litellm.types.proxy.auth.user_roles
Part of LIT-9423
* refactor(types): annotate GenerateRequestBase containers and check_max_budget
Part of LIT-9423
* refactor(types): move GenerateRequestBase and LiteLLM_ObjectPermissionBase into litellm.types.proxy.management_endpoints.request_base
Part of LIT-9423
* refactor(types): annotate user request metadata and check_user_info validators
Part of LIT-9423
* refactor(types): move user request models into litellm.types.proxy.management_endpoints.user_requests
Part of LIT-9423
* refactor(types): move MemberDeleteRequest into litellm.types.proxy.management_endpoints.team_endpoints
Part of LIT-9423
* fix(types): restore main's _types.py content alongside the request_base move
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(sdk): resolve litellm.proxy lazily on attribute access
The layer cleanup stopped import litellm from loading any proxy module, so litellm.proxy was no longer bound and litellm.proxy._types.X raised AttributeError. The module __getattr__ now imports litellm.proxy on first access, which keeps import litellm free of proxy._types and fixes the docs and code-quality checks on main
* fix(sdk): resolve litellm.proxy lazily on attribute access
The layer cleanup stopped import litellm from loading any proxy module, so litellm.proxy was no longer bound and litellm.proxy._types.X raised AttributeError. The module __getattr__ now imports litellm.proxy on first access, which keeps import litellm free of proxy._types and fixes the docs and code-quality checks on main
* fix(sdk): resolve litellm.proxy lazily on attribute access
The layer cleanup stopped import litellm from loading any proxy module, so litellm.proxy was no longer bound and litellm.proxy._types.X raised AttributeError. The module __getattr__ now imports litellm.proxy on first access, which keeps import litellm free of proxy._types and fixes the docs and code-quality checks on main
* style(types): merge request_base re-exports into one import block
Part of LIT-9423
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(types): move LitellmUserRoles and KeyManagementRoutes into litellm.types.proxy.auth.user_roles
Part of LIT-9423
* refactor(types): annotate GenerateRequestBase containers and check_max_budget
Part of LIT-9423
* refactor(types): move GenerateRequestBase and LiteLLM_ObjectPermissionBase into litellm.types.proxy.management_endpoints.request_base
Part of LIT-9423
* refactor(types): annotate user request metadata and check_user_info validators
Part of LIT-9423
* refactor(types): move user request models into litellm.types.proxy.management_endpoints.user_requests
Part of LIT-9423
* fix(types): restore main's _types.py content alongside the request_base move
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(sdk): resolve litellm.proxy lazily on attribute access
The layer cleanup stopped import litellm from loading any proxy module, so litellm.proxy was no longer bound and litellm.proxy._types.X raised AttributeError. The module __getattr__ now imports litellm.proxy on first access, which keeps import litellm free of proxy._types and fixes the docs and code-quality checks on main
* fix(sdk): resolve litellm.proxy lazily on attribute access
The layer cleanup stopped import litellm from loading any proxy module, so litellm.proxy was no longer bound and litellm.proxy._types.X raised AttributeError. The module __getattr__ now imports litellm.proxy on first access, which keeps import litellm free of proxy._types and fixes the docs and code-quality checks on main
* style(types): merge request_base re-exports into one import block
Part of LIT-9423
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(types): move LitellmUserRoles and KeyManagementRoutes into litellm.types.proxy.auth.user_roles
Part of LIT-9423
* refactor(types): annotate GenerateRequestBase containers and check_max_budget
Part of LIT-9423
* refactor(types): move GenerateRequestBase and LiteLLM_ObjectPermissionBase into litellm.types.proxy.management_endpoints.request_base
Part of LIT-9423
* refactor(types): annotate key request containers and drop_blank_team_id
Part of LIT-9423
* refactor(types): move key request models into litellm.types.proxy.management_endpoints.key_requests
Part of LIT-9423
* fix(types): keep MappingProxyType exported from litellm.proxy._types for star importers
Part of LIT-9423
* fix(sdk): resolve litellm.proxy lazily on attribute access
The layer cleanup stopped import litellm from loading any proxy module, so litellm.proxy was no longer bound and litellm.proxy._types.X raised AttributeError. The module __getattr__ now imports litellm.proxy on first access, which keeps import litellm free of proxy._types and fixes the docs and code-quality checks on main
* feat(otel): let a team strip captured message content from its own OTel v2 destination
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(proxy): split the shared callback option conflict check and sync dashboard API types
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(otel): address review feedback on team capture_message_content
Classify capture_message_content as NotSecret in the credential slot registry, inject test exporters through register_exporter_factory instead of patching _exporter_from_spec, type the test helpers, and stop reassigning processor in build_tracer_provider
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(otel): add integration cells for team capture_message_content
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(otel): cover weave_otel and newrelic team destinations in capture_message_content cells
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(otel): stop rejecting client-sent capture_message_content at the request body boundary
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(otel): let a team capture_message_content override the global setting in both directions
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(otel): keep a team's capture_message_content on its own OTel v2 destination
The setting no longer rides the flattened team callback vars, so a sibling destination and a routed provider follow the global mode. Request bodies get the base 400 back, a failure-only entry rejects the setting, and entries for one backend must agree
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(otel): type the capture_message_content callback validation tests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(otel): type the remaining capture_message_content test signatures
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(otel): mark the new capture_message_content test locals Final
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(otel): default tenant capture to callback_settings.otel and keep CaptureMessageContent formatting bare
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(otel): keep CaptureMessageContent a plain str like main
The str-to-Enum switch changed the public type: the config field's type,
repr and model_dump, a constructor that now raised on unknown values, and
unknown env values coerced to no_content. CaptureMessageContent is the plain
str subclass main ships again, the field is a str, and a
captures_span_content helper replaces the enum property. A test pins that a
published preset's capture mode stays the default for an unowned
destination, which is what main forwards.
* test(otel): drop the module-level CaptureMessageContent import the rewritten test no longer uses
* fix(lint): keep the merged branch within main's type budgets
Freeze the capture-mode settings model (LIT015) and read stored logging
entries through one typed sequence helper, so the conflicting-capture checks
add no unknown types.
* fix(otel): reject a destination capture_message_content while OTel v2 is off
The legacy OTel callbacks never read the per-destination setting, so a team
could register no_content and still export prompts and replies under the
global capture mode. Registration now refuses the var unless the proxy runs
with LITELLM_OTEL_V2=true, the same rule the Arize transport and New Relic
routing vars follow.
* test(otel): type the OTel v2 fixtures and the v2-off regression test
* fix(otel): accept only no_content and span_only on a team or key destination
OTel v2 writes captured content only to span attributes, so event_only
behaved like no_content and span_and_event like span_only on a
destination. The proxy-wide setting keeps all four values
* docs(otel): say an omitted capture setting follows the proxy's own callback for that backend
* test(otel): describe the general capture fallback in the unowned destination test
---------
Co-authored-by: mrinal <mrinal@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: yucheng-berri <yucheng@berri.ai>
Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
* refactor(anthropic): move passthrough SSE stream assembly into litellm/llms
Part of LIT-9423
* refactor(anthropic): move raw SSE stream assembly helpers out of proxy guardrails
Part of LIT-9423
* refactor(anthropic): give the anthropic_sse re-exports reasoned noqa codes
Part of LIT-9423
* fix(sdk): resolve litellm.proxy lazily on attribute access
The layer cleanup stopped import litellm from loading any proxy module, so litellm.proxy was no longer bound and litellm.proxy._types.X raised AttributeError. The module __getattr__ now imports litellm.proxy on first access, which keeps import litellm free of proxy._types and fixes the docs and code-quality checks on main
* test(anthropic): cover the raw SSE helpers in stream_assembly
Part of LIT-9423
* refactor(types): move LitellmUserRoles and KeyManagementRoutes into litellm.types.proxy.auth.user_roles
Part of LIT-9423
* refactor(types): annotate GenerateRequestBase containers and check_max_budget
Part of LIT-9423
* refactor(types): move GenerateRequestBase and LiteLLM_ObjectPermissionBase into litellm.types.proxy.management_endpoints.request_base
Part of LIT-9423
* fix(types): restore main's _types.py content alongside the request_base move
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(sdk): resolve litellm.proxy lazily on attribute access
The layer cleanup stopped import litellm from loading any proxy module, so litellm.proxy was no longer bound and litellm.proxy._types.X raised AttributeError. The module __getattr__ now imports litellm.proxy on first access, which keeps import litellm free of proxy._types and fixes the docs and code-quality checks on main
* style(types): merge request_base re-exports into one import block
Part of LIT-9423
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(types): annotate key request containers and drop_blank_team_id
Part of LIT-9423
* fix(sdk): resolve litellm.proxy lazily on attribute access
The layer cleanup stopped import litellm from loading any proxy module, so litellm.proxy was no longer bound and litellm.proxy._types.X raised AttributeError. The module __getattr__ now imports litellm.proxy on first access, which keeps import litellm free of proxy._types and fixes the docs and code-quality checks on main
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(constants): move AUTH_OBJECTS_TARGET into litellm.constants
Part of LIT-9423
* fix(sdk): resolve litellm.proxy lazily on attribute access
The layer cleanup stopped import litellm from loading any proxy module, so litellm.proxy was no longer bound and litellm.proxy._types.X raised AttributeError. The module __getattr__ now imports litellm.proxy on first access, which keeps import litellm free of proxy._types and fixes the docs and code-quality checks on main
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(skills): move NewSkillRequest to litellm.models.skills
Part of LIT-9423
* fix(sdk): resolve litellm.proxy lazily on attribute access
The layer cleanup stopped import litellm from loading any proxy module, so litellm.proxy was no longer bound and litellm.proxy._types.X raised AttributeError. The module __getattr__ now imports litellm.proxy on first access, which keeps import litellm free of proxy._types and fixes the docs and code-quality checks on main
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(terraform): stop sending blocked on litellm_user updates
/user/update writes blocked into the user table upsert, but blocked only
exists as a column on keys, so every litellm_user update failed with a 400
from Prisma. Updates no longer send it. Create sends it only when set to
true, since /user/new applies it to the auto-created key
blocked only applies at creation; litellm_key_block covers changes after that
* fix(terraform): always send blocked on litellm_user create
/user/new fills an omitted blocked from default_internal_user_params, so
leaving it out on create let a proxy-side blocked=true default block the
auto-created key. Create sends the configured value again, including
false, while updates still never send it
* chore(terraform): drop comment on litellm_user create blocked
* fix(terraform): keep litellm_user blocked undeprecated
Create sends blocked again, so it still controls the auto-created key.
Whether to deprecate it in favor of litellm_key_block is left to the
provider maintainers; the docs describe it as creation-only instead
* refactor(anthropic): move prompt cache pricing helper out of the proxy package
Part of LIT-9423
* fix(sdk): resolve litellm.proxy lazily on attribute access
The layer cleanup stopped import litellm from loading any proxy module, so litellm.proxy was no longer bound and litellm.proxy._types.X raised AttributeError. The module __getattr__ now imports litellm.proxy on first access, which keeps import litellm free of proxy._types and fixes the docs and code-quality checks on main
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
The layer cleanup stopped import litellm from loading any proxy module, so litellm.proxy was no longer bound and litellm.proxy._types.X raised AttributeError. The module __getattr__ now imports litellm.proxy on first access, which keeps import litellm free of proxy._types and fixes the docs and code-quality checks on main
* refactor(types): move LitellmUserRoles and KeyManagementRoutes into litellm.types.proxy.auth.user_roles
Part of LIT-9423
* refactor(types): move is_jwt into litellm.types.proxy.auth.user_api_key_auth
Part of LIT-9423
* refactor(auth): alias is_jwt import so JWTHandler.is_jwt is not read as recursive
* refactor(types): move complexity router request models next to their base config
Part of LIT-9423
* test(types): cover the old auto-router import path for the moved request models
Part of LIT-9423
* refactor(anthropic): move prompt cache observation lookup out of the proxy hook
Part of LIT-9423
* test(internal_context): exempt moved prompt cache lookup helper from key-family check
* feat(proxy): require trace IDs per team on LLM, MCP and agent requests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): assert trace ID authorization outcomes
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): clear trace ID type gate errors
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style(proxy): format trace ID type check
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): validate trace ID metadata
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): use read-only trace metadata types
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): skip trace ID metadata validation for teams without dict metadata
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* perf(proxy): check team trace ID setting before route matching
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Each spend-log delete batch and the remaining-rows probe ran inside a
prisma interactive transaction with the default 5s timeout while setting a
30s Postgres statement and lock timeout. A batch that waited on a lock for
more than 5s was closed by the query engine with a 422 and rolled back, and
after three such batches the cleanup run aborted with nothing deleted.
Reuse the partition manager's bounded_tx, which sizes the prisma timeout to
the statement bound plus commit slack, for the delete batch and the probe.
Resolves LIT-8686
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): simplify playground decision endpoint
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): expose both decision API shapes in playground
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): omit undiscovered decision models from examples
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): align decisions form and response views
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: kerry <kerry@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
